Application of Improved genetic algorithm in optimal sensor placement for dynamic test of Harbin Sifangtai Bridge

The research efforts to find best possible sensor locations in structural health monitoring field have received considerable attention recently for those attached to the results of modal parameter identification tightly. Based on the former methods and criteria of optimal sensor placement for modal test, a new method of optimum sensor placement using Improved Genetic Algorithm (IGA) for dynamic test is proposed and applied in detection of Harbin Sifangtai Bridge. The algorithm converges swiftly and has a strong ability to find the best value by improving the constraint condition, thoroughly crossing the auto mutation ratio. According to Effective Independence criterion (EI), Modal Assurance Criterion (MAC) and Modal Kinetic Energy method (MKE), three placement designs are produced. The computational simulation of Harbin Sifangtai Bridge model using all the methods above has been implemented. The simulation results show that accuracy, reliability and efficiency of IGA are much better than traditional Genetic Algorithm and the searching ability of IGA is stronger than classical sequential sensor placement algorithm. Among those methods, three placement designs are adopted in detection of Harbin Sifangtai Bridge. Through the output signal, mode shapes of the bridge are identified by combined method of the NEXT and ERA to evaluate validity of the methods above.